Analysis of Nigerian Children Underweight Nutritional Status Using Geoadditive Cox Models with Gaussian and Binomial Links.
study into geographical variability of nutritional status of children in Nigeria was observed from geostatistical mapping or krigingand the continuous covariate weight for age (underweight) that exhibit pronounced non-linear relationships with the response variable was analysed. Multiple Indicator Cluster Survey 3 (MICS3) data set contains several variables. Only those that are believed to be related to nutritional status were selected and all categorical covariates are effect coded. Children’s nutritional status is a reflection of their overall health, to properly account for the underweight effects on child’s age, sex, their place of resident, mothers’ educational levels, parents’ wealth index, regions and state of the child, geostatistical mapping and additive models were merged using modified Cox model. The geoadditive model allows for fitting and analysis using BayesX software. This builds a statistical model that will help various health agencies in the country in developing a framework, policies and programmes that will improve child health care. Hence, Federal and State governments where the malnutrition is prevalence are hereby advice to be more up and doing towards improving the situation for better future of this great nation of ours.